Iftikhar Imran H, BaHammam Ahmed, Jahrami Haitham, Ioachimescu Octavian
Department of Medicine, Division of Pulmonary, Allergy, Critical Care & Sleep Medicine, Emory University School of Medicine, 613 Michael St., Atlanta, GA, USA.
Atlanta Veterans Affairs Medical Center, Decatur, GA, USA.
Sleep Breath. 2023 Oct;27(5):1759-1768. doi: 10.1007/s11325-023-02780-w. Epub 2023 Jan 30.
Most continuous positive airway pressure (CPAP) machines have built-in manufacturer-specific proprietary algorithms for automatic respiratory event detection (AED) based on very specific respiratory events scoring criteria. With regards to the accuracy of these data from CPAP machines, evidence from the literature seems conflicting, which formed the basis for this meta-analysis.
A meta-analysis was performed on studies that reported Bland-Altman analysis data on agreement (mean bias and limits of agreement [LoA]) of CPAP-determined apnea-hypopnea index (AHI) at therapeutic pressures (AHI) with that determined from simultaneously conducted polysomnograms (AHI).
In six studies, ResMed CPAPs were used, and in another six studies, Respironics CPAPs were used, while only one study used Fisher & Paykel (F&P) CPAPs. The pooled mean AHI bias from ResMed CPAP studies was - 1.01 with pooled LoAs from - 3.55 to 1.54 (I = 17.5%), and from Respironics CPAP studies, pooled mean AHI bias was - 0.59 with pooled LoAs from - 3.22 to 2.05 (I = 0%). Pooled percentage errors (corresponding to LoAs) from four ResMed CPAP studies, four Respironics CPAP studies, and the F&P CPAP study were 73%, 59%, and 112%, respectively. A review of the literature for this meta-analysis also revealed lack of uniformity not only in the CPAP manufacturers' respiratory events scoring criteria but also in that used for PSGs across the studies analyzed.
Even though the pooled results of mean AHI bias suggest good clinical agreement between AHI and AHI, percentage errors calculated in this meta-analysis indicate the possibility of a significant degree of imprecision in the estimation of AHI by CPAP machines.
大多数持续气道正压通气(CPAP)机器都内置了制造商特定的专有算法,用于基于非常具体的呼吸事件评分标准进行自动呼吸事件检测(AED)。关于这些来自CPAP机器的数据的准确性,文献中的证据似乎相互矛盾,这构成了本次荟萃分析的基础。
对报告了CPAP在治疗压力下测定的呼吸暂停低通气指数(AHI)与同时进行的多导睡眠图测定的AHI之间的一致性(平均偏差和一致性界限[LoA])的Bland-Altman分析数据的研究进行荟萃分析。
六项研究使用了瑞思迈CPAP,另外六项研究使用了伟康CPAP,而只有一项研究使用了费雪派克(F&P)CPAP。瑞思迈CPAP研究的合并平均AHI偏差为-1.01,合并LoA为-3.55至1.54(I=17.5%),伟康CPAP研究的合并平均AHI偏差为-0.59,合并LoA为-3.22至2.05(I=0%)。四项瑞思迈CPAP研究和四项伟康CPAP研究以及F&P CPAP研究的合并百分比误差(对应于LoA)分别为73%、59%和112%。对本次荟萃分析的文献回顾还发现,不仅CPAP制造商的呼吸事件评分标准缺乏一致性,而且在所分析的各项研究中用于多导睡眠图的评分标准也缺乏一致性。
尽管平均AHI偏差的汇总结果表明AHI与AHI之间具有良好的临床一致性,但本次荟萃分析中计算的百分比误差表明,CPAP机器在估计AHI时可能存在显著程度的不精确性。